Data‐driven integration of hippocampal CA1 synaptic physiology in silico

The anatomy and physiology of monosynaptic connections in rodent hippocampal CA1 have been extensively studied in recent decades. Yet, the resulting knowledge remains disparate and difficult to reconcile. Here, we present a data‐driven approach to integrate the current state‐of‐the‐art knowledge on the synaptic anatomy and physiology of rodent hippocampal CA1, including axo‐dendritic innervation patterns, number of synapses per connection, quantal conductances, neurotransmitter release probability, and short‐term plasticity into a single coherent resource. First, we undertook an extensive literature review of paired recordings of hippocampal neurons and compiled experimental data on their synaptic anatomy and physiology. The data collected in this manner is sparse and inhomogeneous due to the diversity of experimental techniques used by different groups, which necessitates the need for an integrative framework to unify these data. To this end, we extended a previously developed workflow for the neocortex to constrain a unifying in silico reconstruction of the synaptic physiology of CA1 connections. Our work identifies gaps in the existing knowledge and provides a complementary resource toward a more complete quantification of synaptic anatomy and physiology in the rodent hippocampal CA1 region

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Off-line replay maintains declarative memories in a model of hippocampal-neocortical interactions

During sleep, neural activity in the hippocampus and neocortex seems to recapitulate aspects of its earlier, awake form. This replay may be a substrate for the consolidation of long-term declarative memories, whereby they become independent of the hippocampus and are stored in neocortex. In contrast to storage, other crucial facets of competent long-term memory, such as maintenance of access to stored traces and preservation of their correct interpretation, have received little attention. We investigate long-term episodic and semantic memory in a theoretical model of neocortical-hippocampal interaction. We find that, in the absence of regular hippocampal reactivation, even supposedly consolidated episodic memories are fragile in the face of cortical semantic plasticity. Replay allows access to episodes stored in the hippocampus to be maintained, by keeping them in appropriate register with changing neocortical representations. Hippocampal storage and replay also has a constructive role in the recall of structured, semantic information

A familiarity-based learning procedure for the establishment of place fields in area CA3 of the rat hippocampus

That familiarity should gate learning is a neurobiological and computational commonplace, and has been particularly investigated in the context of the hippocampus. We show its critical importance in continuous attractor models, using the formation of place fields in hippocampal area CA3 as an example. Without it, biased sampling of places in an environment, coming from purely random exploration, leads to degenerate attractors and prevents the formation of place fields. Conversely, appropriate use of familiarity information during learning can counteract the sampling bias, resulting in a normal place cell representation